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| Registros recuperados : 2 | |
| 2. |  | DALLAGNOL, L. J.; NAVARINI, L.; UGALDE, M. G.; BALARDIN, R. S.; CATELLAM, R. Utilizacao de acibenzolar-S-Methyl para controle de doencas foliares da soja. Summa Phytopathologica, Botucatu, v. 32, n. 3, p. 255-259, jul./set. 2006.| Biblioteca(s): Epagri-Sede. |
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| Registros recuperados : 2 | |
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Registro Completo
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
03/08/2022 |
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Data da última atualização: |
03/08/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
BARTH, E.; RESENDE, J. T. V.; MARIGUELE, K. H.; RESENDE, M. D. V.; SILVA, A. L. B. R.; RU, S. |
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Título: |
Multivariate analysis methods improve the selection of strawberry genotypes with low cold requirement. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Scientific Reports, New York, 2022. |
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Idioma: |
Inglês |
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Conteúdo: |
Methods of multivariate analysis is a powerful approach to assist the initial stages of crops genetic
improvement, particularly, because it allows many traits to be evaluated simultaneously. In this
study, heat-tolerant genotypes have been selected by analyzing phenotypic diversity, direct and
indirect relationships among traits were identifed, and four selection indices compared. Diversity
was estimated using K-means clustering with the number of clusters determined by the Elbow
method, and the relationship among traits was quantifed by path analysis. Parametric and nonparametric indices were applied to selected genotypes using the magnitude of genotypic variance,
heritability, genotypic coefcient of variance, and assigned economic weight as selection criteria.
The variability among materials led to the formation of two non-overlapping clusters containing 40
and 154 genotypes. Strong to moderate correlations were found between traits with direct efect of
the number of commercial fruit on the mass of commercial fruit. The Smith and Hazel index showed
the greatest total gains for all criteria; however, concerning the biochemical traits, the Mulamba
and Mock index showed the highest magnitudes of predicted gains. Overall, the K-means clustering,
correlation analysis, and path analysis complement the use of selection indices, allowing for selection
of genotypes with better balance among the assessed traits. |
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Thesagro: |
none. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02000naa a2200193 a 4500
001 1132146
005 2022-08-03
008 2022 bl uuuu u00u1 u #d
100 1 $aBARTH, E.
245 $aMultivariate analysis methods improve the selection of strawberry genotypes with low cold requirement.$h[electronic resource]
260 $c2022
520 $aMethods of multivariate analysis is a powerful approach to assist the initial stages of crops genetic improvement, particularly, because it allows many traits to be evaluated simultaneously. In this study, heat-tolerant genotypes have been selected by analyzing phenotypic diversity, direct and indirect relationships among traits were identifed, and four selection indices compared. Diversity was estimated using K-means clustering with the number of clusters determined by the Elbow method, and the relationship among traits was quantifed by path analysis. Parametric and nonparametric indices were applied to selected genotypes using the magnitude of genotypic variance, heritability, genotypic coefcient of variance, and assigned economic weight as selection criteria. The variability among materials led to the formation of two non-overlapping clusters containing 40 and 154 genotypes. Strong to moderate correlations were found between traits with direct efect of the number of commercial fruit on the mass of commercial fruit. The Smith and Hazel index showed the greatest total gains for all criteria; however, concerning the biochemical traits, the Mulamba and Mock index showed the highest magnitudes of predicted gains. Overall, the K-means clustering, correlation analysis, and path analysis complement the use of selection indices, allowing for selection of genotypes with better balance among the assessed traits.
650 $anone
700 1 $aRESENDE, J. T. V.
700 1 $aMARIGUELE, K. H.
700 1 $aRESENDE, M. D. V.
700 1 $aSILVA, A. L. B. R.
700 1 $aRU, S.
773 $tScientific Reports, New York, 2022.
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